Hybrid Flow Shop Scheduling Problems Using Improved Fireworks Algorithm for Permutation

Abstract

Prior studies are lacking which address permutation flow shop scheduling problems and hybrid flow shop scheduling problems together to help firms find the optimized scheduling strategy. The permutation flow shop scheduling problem and hybrid flow shop scheduling problems are important production scheduling types, which widely exist in industrial production fields. This study aimed to acquire the best scheduling strategy for making production plans. An improved fireworks algorithm is proposed to minimize the makespan in the proposed strategies. The proposed improved fireworks algorithm is compared with the fireworks algorithm, and the improvement strategies include the following: (1) A nonlinear radius is introduced and the minimum explosion amplitude is checked to avoid the waste of optimal fireworks; (2) The original Gaussian mutation operator is replaced by a hybrid operator that combines Cauchy and Gaussian mutation to improve the search ability; and (3) An elite group selection strategy is adopted to reduce the computing costs. Two instances from the permutation flow shop scheduling problem and hybrid flow shop scheduling problems were used to evaluate the improved fireworks algorithm's performance, and the computational results demonstrate the improved fireworks algorithm's superiority.

Integrated Optimization Approach of Hybrid Flow-Shop Scheduling Based on Process Set

“…Constraint (9) indicates that the weight of each batch cannot exceed the processing threshold of the batch machine. Constraint (10) indicates that the processing time of each batch set depends on the batch weight and basic melting time constant. Constraint (11) indicates that the start time of each batch process set is earlier than the completion time of all its predecessor processes.…”

“…This job first divides the job cluster based on the number of batch machines (each job cluster is processed on only one batch), and then groups batches according to the threshold method in each job cluster. The processing time of each batch machine is determined according to Constraint (10). Each job cluster, as shown in FIGURE 4, is grouped using the rules of Early Release Time Fit, assuming that there are a total of n jobs, where Oi,4 can be processed on the batch machine.…”

“…The method mainly includes a heuristic approach and hybrid intelligence optimization algorithm. For the integrated optimization model of permutation flow shop scheduling problems with HFS, Pang et al developed an improved fireworks algorithm to minimize the makespan [10]. Mirsanei et al proposed a novel simulated annealing algorithm to produce a reasonable manufacturing schedule within an acceptable computational time for solving the HFS with sequence-dependent setup times [11].…”

Flow Shop Providing Frequency Regulation Service in Electricity Market

“…Meanwhile, the way to improve solving algorithm is intensively studied recently [30][31][32][33][34]. In the literature, new algorithms or methods are proposed for more optimal scheduling results or more efficient computation.…”

“…Analysis and discussion are presented below. Give that most research [26][27][28][29][30][31][32][33][34] defines both optimizations to be nonlinear programming and addresses them by heuristic algorithms, we also adopted genetic algorithm to solve them.…”